Tushar Jain

Synergy of evolutionary algorithm and socio-political process for global optimization

This paper proposes a hybrid approach by combining the evolutionary optimization based genetic algorithm (GA) and socio-political process based colonial competitive algorithm (CCA). The performance of hybrid algorithm is illustrated using standard test functions in comparison to basic CCA method. Since the CCA method is newly developed, very little research work has been undertaken to deal with curse of dimensionality and to improve the convergence speed and accuracy of the basic CCA algorithm. The proposed CCA-GA algorithm is then used to tune a PID controller for a real time ball and beam system. Simulation results were reported and the hybrid algorithm indeed has established superiority over the basic algorithms with respect to set of functions considered and it can easily be extended for other global optimization problems.

On implementing on-line designed controller for smooth interconnection in the behavioral framework

Abstract In the behavioral setting, a controller is designed using the behavior of the plant, and the given desired behavior. Further, the synthesized controller makes an interconnection with the plant such that the interconnected system satisfies the desired behavior. However, at the time of interconnection it might not be possible. Here, first we design an on-line controller using the real-time measurements generated by the plant, and the given desired behavior. Secondly, we show a way to implement this on-line designed controller such that at the time of interconnection, the closed-loop satisfies the desired behavior. The novelty of the demonstrated approach lies in the fact that we do not have any a priori information about the plant in real-time.

Human Spermatozoa Quantitative Proteomic Signature Classifies Normo- and Asthenozoospermia

Scarcely understood defects lead to asthenozoospermia, which results in poor fertility outcomes. Incomplete knowledge of these defects hinders the development of new therapies and reliance on interventional therapies, such as in vitro fertilization, increases. Sperm cells, being transcriptionally and translationally silent, necessitate the proteomic approach to study the sperm function. We have performed a differential proteomics analysis of human sperm and seminal plasma and identified and quantified 667 proteins in sperm and 429 proteins in seminal plasma data set, which were used for further analysis. Statistical and mathematical analysis combined with pathway analysis and self-organizing maps clustering and correlation was performed on the data set. It was found that sperm proteomic signature combined with statistical analysis as opposed to the seminal plasma proteomic signature can differentiate the normozoospermic versus the asthenozoospermic sperm samples. This is despite the results that some of the seminal plasma proteins have big fold changes among classes but they fall short of statistical significance. S-Plot of the sperm proteomic data set generated some high confidence targets, which might be implicated in sperm motility pathways. These proteins also had the area under the curve value of 0.9 or 1 in ROC curve analysis. Various pathways were either enriched in these proteomic data sets by pathway analysis or they were searched by their constituent proteins. Some of these pathways were axoneme activation and focal adhesion assembly, glycolysis, gluconeogenesis, cellular response to stress and nucleosome assembly among others. The mass spectrometric data is available via ProteomeXchange with identifier PXD004098.

A Novel Approach to Real-Time Fault Accommodation in NREL's 5-MW Wind Turbine Systems

This paper presents a real-time mechanism to tolerate faults occurring in a wind turbine (WT) system. This system is a FAST coded simulator designed by the U.S. National Renewable Energy Laboratorys (NRELs) National Wind Turbine Center. The demonstrated mechanism lies under the taxonomy of active fault-tolerant control (AFTC) systems, namely the projection-based approach. In the proposed approach, we do not use any a priori information about the model of the turbine in real-time. In fact, we use the online measurements generated by WT. Based on the given control objectives, and the observed measurements, an occurring fault is accommodated by reconfiguring the controller such that the turbine generates the rated power even under faulty conditions. Second, no use of an explicit fault-diagnosis module is seen in this approach. Therefore, the fault accommodation delay in the proposed AFTC structure is smaller than the delay as experienced in the traditional structure of AFTC systems.

Synergy of canonical control and unfalsified control concept to achieve fault tolerance

Abstract behavioral theoretical explanation of active fault tolerant control (FTC) problem is proposed in this note. Precisely, we present the concept of canonical controller and unfalsified control in behavioral context. The synergy of two control concepts re-configures the controller such that the system is tolerant to unknown faults. The main feature of the resulting FTC system is that it does not utilize any model-based fault detection and isolation procedure on-line. Therefore, it relies solely on the time-valued trajectories generated by the unknown plant in the closed-loop environment. In our approach to FTC, these trajectories formulate the control specifications that characterize certain desired behavior. Consequently, the controller re-designing process commence when this desired behavior is not satisfied.

Bacterial Foraging Optimized Hybrid Fuzzy Precompensated PD Control of Two Link Rigid-Flexible Manipulator

Light-weight flexible arms will most likely constitute the next generation robots due to their large payload carrying capacities at high speeds and less power demand. Control problem of robots with flexible members is more complex compared to rigid robots due to vibrations during the motion. This paper presents the social foraging behavior of Escherichia coli bacteria to optimize hybrid Fuzzy Precompensated Proportional — Derivative (PD) controller in trajectory control of two link rigid-flexible manipulator. Numerical simulation using the dynamic model of the two link rigid-flexible manipulator shows the effectiveness of the approach in trajectory tracking problems and the use of fuzzy precompensation has superior performance in terms of improvement in transient and steady state response, robustness to variations in loading conditions and ease to use in practice. Comparative evaluation with respect to genetic algorithm based optimization is presented to validate the controller design. The results present...

Hybrid bacterial foraging and particle swarm optimisation for fuzzy precompensated control of flexible manipulator

This paper presents hybrid approach combining the social foraging behaviour of Escherichia coli bacteria and particle swarm optimisation for optimising hybrid fuzzy precompensated proportional-derivative (PD) controller in trajectory control of two-link rigid-flexible manipulator. Numerical simulation using the dynamic model of the two-link rigid-flexible manipulator shows the effectiveness of the approach in trajectory tracking problems. The use of fuzzy precompensation has superior performance in terms of improvement in transient and steady state response, robustness to variations in loading conditions and ease to use in practice. Comparative evaluation with respect to genetic algorithm, particle swarm and bacterial foraging-based optimisation is presented to validate the controller design. The proposed algorithm performs local search through the chemotactic movement operation of bacterial foraging whereas the global search over the entire search space is accomplished by a particle swarm operator and so satisfactory tracking precision could be achieved using the approach.

Active Fault-Tolerant Control Systems: A Behavioral System Theoretic Perspective

The book introduces novel algorithms for designing fault-tolerant control (FTC) systems using the behavioral system theoretic approach, and presents a demonstration of successful novel FTC mechanisms on several benchmark examples. The authors also discuss a new transient management scheme, which is an essential requirement for the implementation of active FTC systems, and two data-driven methodologies that are broadly classified as active FTC systems: the projection-based approach and the online-redesign approach. These algorithms do not require much a priori information about the plant in real-time, and in addition this novel implementation of active FTC systems circumvents various weaknesses induced by using a diagnostic module in real-time. The book provides graduate students taking masters and doctoral courses in mathematics, control, and electrical engineering an excellent stepping-stone for their research. It also appeals to practitioners interested to apply innovative fail-safe control techniques.

A hybrid genetically-bacterial foraging algorithm converged by particle swarm optimisation for global optimisation

The social foraging behaviour of Escherichia coli bacteria and the effectiveness of genetic operators have recently been combined to develop a hybridised algorithm for distributed optimisation and control. The classical algorithms have their importance in solving real-world optimisation problems. Hybridisation of two algorithms is gaining popularity among researchers to explore the area of optimisation. This paper proposes a novel algorithm which hybridises the best features of three basic algorithms, i.e., genetic algorithm (GA), bacterial foraging (BF) and particle swarm optimisation (PSO) as genetically bacterial swarm optimisation (GBSO). The hybridisation is carried out in two phases; first, the diversity in searching the optimal solution is increased using selection, crossover and mutation operators. Secondly, the search direction vector is optimised using PSO to enhance the convergence rate of the fitness function in achieving the optimality. The proposed algorithm is tested on a set of functions which are then compared with the basic algorithms. Simulation results were reported and the proposed algorithm indeed has established superiority over the basic algorithms with respect to the set of functions considered and it can easily be extended for other global optimisation problems.

Trajectory-based real-time control of an electrical circuit against unknown faults

Abstract This paper presents a trajectory-based online control reconfiguration mechanism against unknown fault occurring in an electric circuit. First, we demonstrate the modeling of an electric circuit by taking the time-trajectory viewpoint, where no a priori input–output partition has been made. The uniqueness of this viewpoint lies in the fact that it deals only with variables that describe the system without any dedicated (external or internal -type) representation. Subsequently, we illustrate a novel real-time fault-tolerant control (FTC) strategy based on this trajectory standpoint, which does not require an explicit model-based fault diagnosis unit. Instead, the controller is reconfigured directly based on the trajectories generated by the system in real-time, and the given control specifications. In this way, we efficiently excrete the shortcomings that are often seen in model-based fault-tolerant systems. The proposed FTC method is effectively demonstrated on an RLC circuit.